数量结构-活动关系
背景(考古学)
生物信息学
遗传毒性
计算机科学
生化工程
数据挖掘
计算生物学
机器学习
化学
工程类
生物
毒性
古生物学
生物化学
有机化学
基因
作者
Enrico Mombelli,Giuseppa Raitano,Emilio Benfenati
出处
期刊:Methods in molecular biology
日期:2022-01-01
卷期号:: 149-183
被引量:5
标识
DOI:10.1007/978-1-0716-1960-5_7
摘要
Information on genotoxicity is an essential piece of information in the framework of several regulations aimed at evaluating chemical toxicity. In this context, QSAR models that can predict Ames genotoxicity can conveniently provide relevant information. Indeed, they can be straightforwardly and rapidly used for predicting the presence or absence of genotoxic hazards associated with the interactions of chemicals with DNA. Nevertheless, and despite their ease of use, the main interpretative challenge is related to a critical assessment of the information that can be gathered, thanks to these tools. This chapter provides guidance on how to use freely available QSAR and read-across tools provided by VEGA HUB and on how to interpret their predictions according to a weight-of-evidence approach.
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